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We study the problem of minimizing the average of a large number of smooth convex functions penalized with a strongly convex regularizer.
A dual coordinate descent method for large-scale linear svm
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, and S. Sundararajan · 2008
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A dual coordinate descent method for large-scale linear svm
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S Sathiya Keerthi, and S Sundararajan · 2008
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Parallel coordinate descent for L1-regularized loss minimization
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, and Carlos Guestrin · 2011
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A first-order primal-dual algorithm for convex problems with applications to imaging
Antonin Chambolle and Thomas Pock · 2011
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Stochastic methods for ℓ 1 \ell_{1} -regularized loss minimization
Shai Shalev-Shwartz and Ambuj Tewari · 2011
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Efficiency of coordinate descent methods on huge-scale optimization problems
Yurii Nesterov · 2012
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Parallel coordinate descent methods for big data optimization problems
Peter Richtárik and Martin Takáč · 2012
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Proximal stochastic dual coordinate ascent
Shai Shalev-Shwartz and Tong Zhang · 2012
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Accelerated, parallel and proximal coordinate descent
Olivier Fercoq and Peter Richtárik · 2013
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Smooth minimization of nonsmooth functions by parallel coordinate descent
Olivier Fercoq and Peter Richtárik · 2013
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Accelerating stochastic gradient descent using predictive variance reduction
Rie Johnson and Tong Zhang · 2013
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Parallel boosting with momentum
Indraneel Mukherjee, Kevin Canini, Rafael Frongillo, and Yoram Singer · 2013
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Gradient methods for minimizing composite objective function
Yurii Nesterov · 2013
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Distributed coordinate descent method for learning with big data
Peter Richtárik and Martin Takáč · 2013
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On optimal probabilities in stochastic coordinate descent methods
Peter Richtárik and Martin Takáč · 2013
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Minimizing finite sums with the stochastic average gradient
Mark Schmidt, Nicolas Le Roux, and Francis Bach · 2013
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Accelerated mini-batch stochastic dual coordinate ascent
Shai Shalev-Shwartz and Tong Zhang · 2013
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Stochastic dual coordinate ascent methods for regularized loss
Shai Shalev-Shwartz and Tong Zhang · 2013
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Communication-efficient distributed dual coordinate ascent
Martin Jaggi, Virginia Smith, Martin Takáč, Jonathan Terhorst, Sanjay Krishnan, Thomas Hofmann, and Michael I. Jordan · 2014
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mS2GD: Mini-batch semi-stochastic gradient descent in the proximal setting
Jakub Konečný, Jie Lu, Peter Richtárik, and Martin Takáč · 2014
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S2CD: Semi-stochastic coordinate descent
Jakub Konečný, Zheng Qu, and Peter Richtárik · 2014
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S2GD: Semi-stochastic gradient descent methods
Jakub Konečný and Peter Richtárik · 2014
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An accelerated proximal coordinate gradient method and its application to regularized empirical risk minimization
Qihang Lin, Zhaosong Lu, and Lin Xiao · 2014
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Mini-batch primal and dual methods for SVMs
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Inexact block coordinate descent method: complexity and preconditioning
Rachael Tappenden, Peter Richtárik, and Jacek Gondzio · 2013
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Trading computation for communication: Distributed stochastic dual coordinate ascent
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Analysis of distributed stochastic dual coordinate ascent
Tianbao Yang, Shenghuo Zhu, and Yuanqing Lin · 2013
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Fast distributed coordinate descent for minimizing non-strongly convex losses
Olivier Fercoq, Zheng Qu, Peter Richtárik, and Martin Takáč · 2014
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Incremental majorization-minimization optimization with application to large-scale machine learning
Julien Mairal · 2014
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A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints
Ion Necoara and Andrei Patrascu · 2014
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
Peter Richtárik and Martin Takáč · 2014
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Separable approximations and decomposition methods for the augmented lagrangian
Rachael Tappenden, Peter Richtárik, and Burak Büke · 2014
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A proximal stochastic gradient method with progressive variance reduction
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Stochastic primal-dual coordinate method for regularized empirical risk minimization
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Stochastic optimization with importance sampling
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